I wonder if moving towards an auction-type model for driver rates could lower costs. Drivers submit their per-mile rate for the day, and in addition to proximity, a job is rewarded to the lowest bidding driver.
I'm not really sure - I know they have experimented a lot with different models, and at one point recently I think they tried something like that in CA, because it made them more IC-like and thus maybe not subject to employee classification.
One thing that sticks out to me from the data is that rates and utilization seem surprisingly consistent in the couple of years before Covid. Most drivers seem to have an idea of what they are getting into. Anecdotally, some part time drivers show up disproportionately for big events where they know they will get the huge surge pricing, and that seems to show up in the Cornell study, which finds that a few drivers are pulling down fairly high per-hour rates.
Total comp is basically per mile rate * utilization, so once you start messing with utilization between drivers, it gets pretty complicated in my mind. I think utilization must end up mattering much more than per mile rate - I think the per mile rates only ever really go way up when there is a shortage of drivers, during peak travel times or during an event (or now, during a pandemic).
That's why I don't like MBAs. They love talking and publishing copious amounts of research with such baseless claims and comparisons. Comparing Uber with the airline industry and calling the software worthless tells me more about the author than Uber. Ever heard of a marketplace on the web?
You don't include the costs of the car in the cost of the trip. Cars are 2nd biggest cost next to drivers. The cost of operating those cars are paid by drivers, not Uber. This is probably why the 41% figure from 2016 is closer to reality. Your graphs also show to gradual losses due to Uber in the taxi industry since 2014, with your Uber stats starting at 2018. Now go get some Uber stock I guess while you take Uber slave driver rides.
That's not correct. The wages to drivers found in those studies are *net* of the cost of operating the cars. That's why I say the studies are so sensitive to the method you use to estimate the cost of operating the car. The gross payments to the drivers are far higher than the net estimated compensation of course.
If you have an issue with the methodology of the studies, you would have to take it up with the people who carried them out. I tried to weight it toward the Parrott and Reich study in New York specifically because they were pro-minimum wage and most likely to be liberal about how they estimated operating costs, and New York is bound to have the highest operating costs of any market anyway.
As I noted, the Chicago ridesharing data starts in 2018, but you can look at the New York data, which goes all the way back to 2014. I left it out of this piece because it tells the same story and is mostly redundant, but it's all right there at the link to the original dashboard.
Yes, and to be clear, Uber does break out the different businesses. Just based on what we know about the economics of the Mobility business, it's likely it was profitable before Covid, as they reported. I didn't read through all of the transcripts but I got the sense that they think there is some synergy between Eats and Mobility, in terms of acquiring customers and drivers, and that justifies spending to go after Eats.
The point of the analysis is to see if we can figure out what kind of business it is without having to rely on their segmentation and reporting, so that's why I glossed over their reporting a bit. But I generally agree with everything you said.
Thanks! You are right about the geographic markets - mixing in some new loss-making markets would distort the whole picture. I was in a smaller European tourist city a few months before Covid where Uber had just launched, so those markets are definitely out there. We do know the overall TAM for ride-hailing skews toward the really big metros where a lot of people don't have cars, where Uber has been since the beginning (2012) but all the same, yes, any new markets at all where they lose money would distort it quite a bit.
I wonder if moving towards an auction-type model for driver rates could lower costs. Drivers submit their per-mile rate for the day, and in addition to proximity, a job is rewarded to the lowest bidding driver.
I'm not really sure - I know they have experimented a lot with different models, and at one point recently I think they tried something like that in CA, because it made them more IC-like and thus maybe not subject to employee classification.
One thing that sticks out to me from the data is that rates and utilization seem surprisingly consistent in the couple of years before Covid. Most drivers seem to have an idea of what they are getting into. Anecdotally, some part time drivers show up disproportionately for big events where they know they will get the huge surge pricing, and that seems to show up in the Cornell study, which finds that a few drivers are pulling down fairly high per-hour rates.
Total comp is basically per mile rate * utilization, so once you start messing with utilization between drivers, it gets pretty complicated in my mind. I think utilization must end up mattering much more than per mile rate - I think the per mile rates only ever really go way up when there is a shortage of drivers, during peak travel times or during an event (or now, during a pandemic).
That's why I don't like MBAs. They love talking and publishing copious amounts of research with such baseless claims and comparisons. Comparing Uber with the airline industry and calling the software worthless tells me more about the author than Uber. Ever heard of a marketplace on the web?
You don't include the costs of the car in the cost of the trip. Cars are 2nd biggest cost next to drivers. The cost of operating those cars are paid by drivers, not Uber. This is probably why the 41% figure from 2016 is closer to reality. Your graphs also show to gradual losses due to Uber in the taxi industry since 2014, with your Uber stats starting at 2018. Now go get some Uber stock I guess while you take Uber slave driver rides.
That's not correct. The wages to drivers found in those studies are *net* of the cost of operating the cars. That's why I say the studies are so sensitive to the method you use to estimate the cost of operating the car. The gross payments to the drivers are far higher than the net estimated compensation of course.
If you have an issue with the methodology of the studies, you would have to take it up with the people who carried them out. I tried to weight it toward the Parrott and Reich study in New York specifically because they were pro-minimum wage and most likely to be liberal about how they estimated operating costs, and New York is bound to have the highest operating costs of any market anyway.
As I noted, the Chicago ridesharing data starts in 2018, but you can look at the New York data, which goes all the way back to 2014. I left it out of this piece because it tells the same story and is mostly redundant, but it's all right there at the link to the original dashboard.
Yes, and to be clear, Uber does break out the different businesses. Just based on what we know about the economics of the Mobility business, it's likely it was profitable before Covid, as they reported. I didn't read through all of the transcripts but I got the sense that they think there is some synergy between Eats and Mobility, in terms of acquiring customers and drivers, and that justifies spending to go after Eats.
The point of the analysis is to see if we can figure out what kind of business it is without having to rely on their segmentation and reporting, so that's why I glossed over their reporting a bit. But I generally agree with everything you said.
Thanks! You are right about the geographic markets - mixing in some new loss-making markets would distort the whole picture. I was in a smaller European tourist city a few months before Covid where Uber had just launched, so those markets are definitely out there. We do know the overall TAM for ride-hailing skews toward the really big metros where a lot of people don't have cars, where Uber has been since the beginning (2012) but all the same, yes, any new markets at all where they lose money would distort it quite a bit.
I’ll try! Thanks for reading!